Feature tracking from an image sequence using affine invariance and Hough transform

Feature point tracking from an image sequence is an important step in many methods of image understanding including shape from motion[1,2] and mobile robot navigation[5]. Assuming an affine camera model, this paper proposed a new tracking method using affine invariance. Any 3D feature point can have unique coordinates with reference to an affine basis and the affine coordinates are invariant to affine transformations: camera rotations and translations. The images of a set of 4 control points defining an affine basis are tracked in an image sequence using a conventional method. Under this assumption, given a feature point in any image, its locus in the first image(or any other image) is a straight line. The straight lines of the corresponding features from the image sequence will intersect at a point, the corresponding feature point, in the first image. A Hough transform technique is designed to detect this intersection point and track the corresponding feature points in the image sequence. This technique is suitable for tracking a large number of feature points. Its performance is practically unaffected by missing features in some images and large motion steps. Accurate and reliable results had been obtained in real experiments using the method.